Recommend Colab + GPUs for transfer learning episode

[qualiaMachine]

The pretrained model(s) we use in the transfer learning episode are quite large (relative to prev. examples in workshop at least). To speed things up, I'm going to recommend my learners use Google Colab for that episode, with the GPU enabled. I added this recommendation as a "spoiler" block so it doesn't take up too much of the episode real estate, for those that want to stick to the local setup. Those who wish to use Colab should follow the instructions added to the spoiler block.

On a related note, I will be adding another exercise to this lesson to explore finetuning. This is another motivating reason for why I really think a GPU is called for here. Plus, this is an opportunity to explain the importance of GPUs to learners.

[github-actions]

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⏱️ Updated at 2025-05-15 20:04:00 +0000

[carschno]

I am very hesitant to actively recommend proprietary products as part of the teaching, even though I understand the advantages. We also refer to Binder instead, although we need to make sure it serves the purpose.
Anyway, running things locally would remain my preference, and is probably becoming a smaller problem.

[carschno]

TODO: replace the Google Colab notebook solution with Binder. Requires testing the whole setup.

[carschno]

As sketched out in #173 (comment), we should have general hints for moving to a cloud-based solution for the entire lesson. The comment lists candidates with pros and cons, discussing speed, business/price model, availability (including services for specific communities and countries).